ABSTRAK Tumbuhan yang berpotensi sebagai pestisida nabati, diantaranya sirsak (Annona muricata), kirinyuh (Choromoleana odorata) dan lengkuas (Alpinia galanga). Tujuan penelitian ini adalah menguji efektivitas ekstrak daun sirsak, kirinyuh dan rimpang lengkuas terhadap pertumbuhan koloni Colletotrichum acutatum, penyebab penyakit antraknosa pada tanaman cabai, secara in vitro. Penelitian dilaksanakan di laboratorium Fakultas Pertanian Universitas Siliwangi mulai bulan Juli sampai Agustus 2016. Rancangan Percobaan menggunakan Rancangan Acak Lengkap yang terdiri dari 9 perlakuan dengan 3 ulangan. Perlakuan terdiri dari : A = kontrol; B = ekstrak daun sirsak 0,5%; C = ekstrak daun sirsak 1%; D = ekstrak daun kirinyuh 0,5%; E = ekstrak daun kirinyuh 1%; F = ekstrak rimpang lengkuas 0,5%; G = ekstrak rimpang lengkuas 1%; H = campuran ekstrak daun sirsak, kirinyuh dan rimpang lengkuas 0,5%; dan I = campuran ekstrak daun sirsak, kirinyuh dan rimpang lengkuas 1%. Hasil penelitian menunjukkan bahwa campuran ekstrak daun sirsak, kirinyuh dan rimpang lengkuas 1% efektif dalam menghambat pertumbuhan koloni C.acutatum, pada masa inkubasi 7 hari sebesar 66,19% dan pada masa inkubasi 14 hari sebesar 69,94%. Ketiga ekstrak pestisida nabati tersebut memiliki potensi sebagai anti jamur C. acutatum. ABSTRACT Several plants that are potentially used as bio-pesticides are soursop, siam weed, and galangal. The research objective was to find out the effectiveness of leaf extract of soursop and C. odorata, and extract of galangal rhizome in inhibiting the growth of Colletotrichum acutatum colonies, causing antracnose on chilli, in in vitro. The experiment was conducted in the laboratory of Agriculture Faculty, Universitas Siliwangi Tasikmalaya from July until August 2016. The research design used was a completely randomized design consisted of nine treatments and three replications. The treatments were A (control); B (soursop leaf extract, 0,5%); C (soursop leaf extract, 1%); D (C. odorata leaf extract, 0,5 %); E (C. odorata leaf extract 1%); F (galangal rhizome extract 0,5%); G (galangal rhizome extract 1%); H (mixture of soursop leaf extract, C. odorata leaf extract, and galangal rhizome extract each 0,5%; and I (mixture of soursop leaf extract, C. odorata leaf extract, and galangal rhizome extract each 1%). The results

Postbloom fruit drop (PFD) of citrus, caused by Colletotrichum acutatum, produces orange-brown lesions on petals and results in premature fruit drop and the retention of calyces. C. gloeosporioides is common in groves and causes postharvest anthracnose on fruit. Both diseases are controlled effectively by the fungicide benomyl in research fields and commercial orchards. Highly sensitive and resistant isolates of C. gloeosporioides were found, whereas all isolates of C. acutatum tested were moderately resistant. In preliminary studies conducted in vitro with three isolates of each, mycelial growth of sensitive isolates of C. gloeosporioides was inhibited completely by benomyl (Benlate 50 WP) at 1.0 μg/ml, whereas resistant isolates grew well at 10 μg/ml. Growth of all isolates of C. acutatum was inhibited by about 55% at 0.1 μg/ml and by 80% at 1.0 μg/ml. Spore germination of C. acutatum was inhibited more at 0.1 μg/ml than at 1.0 μg/ml or higher concentrations. In all, 20 isolates of C. acutatum from 17 groves and 20 isolates of C. gloeosporioides from 7 groves were collected from locations with different histories of benomyl usage in São Paulo, Brazil, and Florida, United States. Benomyl at 1.0 μg/ml completely inhibited growth of 133 isolates of C. gloeosporioides, with the exception of 7 isolates that were highly resistant to the fungicide, whereas all isolates of C. acutatum were only partially inhibited at 0.1 and 1.0 μg/ml. Analysis of variance indicated that the sensitivity of the isolates of C. acutatum was not affected by benomyl usage or grove of origin, and country of origin had only minor effects. No highly resistant or sensitive isolate of C. acutatum was recovered. Partial sequencing of the β-tubulin gene did not reveal nucleotide substitutions in codons 198 or 200 in C. acutatum that usually are associated with benomyl resistance in other fungi.

Colletotrichum spp. cause anthracnose in various fruits post‐harvest and are a particularly important problem in tropical and subtropical fruits. The disease in fruits of avocado, guava, papaya, mango and passion fruit has been reported to be caused by C. gloeosporioides, and in banana by C. musae. In subtropical and temperate crops such apple, grape, peach and kiwi, the disease is caused by C. acutatum. The variation in pathogenic, morphological, cultural and molecular characteristics of Brazilian isolates of Colletotrichum acutatum Simmonds and isolates from post‐harvest decays of avocado, banana, guava, papaya, mango and passion fruit was evaluated. The fruits were inoculated with mycelium of C. acutatum, Colletotrichum spp. and C. musae on a disc of potato dextrose agar. The morphological, cultural and molecular characteristics studied were conidia morphology, colony growth at different temperatures, colony coloration and PCR with primers CaInt2 and ITS4 for C. acutatum and CgInt and ITS4 for C. gloeosporioides. C. acutatum was pathogenic to avocado, guava, papaya, mango and passion fruit, but it was not pathogenic to banana. The morphological, cultural and molecular studies indicated that the avocado, papaya, mango and passion fruit isolates were C. gloeosporioides. The natural guava isolate was identified as C. acutatum, which had not been found previously to produce anthracnose symptoms on guava in Brazil.

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Succinate dehydrogenase inhibitors (SDHIs) constitute a mainstay in management of gray mold caused by Botrytis cinerea in strawberry and several other crops. In this study, we investigated the risks of resistance development to three newer SDHIs (i.e., fluopyram, fluxapyroxad, and penthiopyrad) and their cross-resistance with the previously registered boscalid. We investigated the mutations in the SdhB subunit and evaluated their impact on microbial fitness in field populations of B. cinerea. Amino acid substitutions associated with resistance to SDHIs were detected at three codons of the SdhB subunit (BH272R/Y/L, BP225F, and BN230I) in the succinate dehydrogenase gene of field isolates from Florida. The BH272R, BH272Y, BH272L, BP225F, and BN230I mutations were detected at frequencies of 51.5, 28.0, 0.5, 2.5, and 4%, respectively. Strong cross-resistance patterns were evident between boscalid and fluxapyroxad and penthiopyrad but not with fluopyram, except in BH272L, BP225F, and BN230I mutants. All five mutations conferred moderate to very high resistance to boscalid whereas the BH272Y conferred resistance to fluxapyroxad and penthiopyrad. The BH272L, BN230I, and BP225F mutations conferred high resistance to all four SDHIs tested. Resistance monitoring following the first use of penthiopyrad in strawberry fields in Florida in 2013 suggests potential for quick selection for highly resistant populations and warrants careful use of the newer SDHIs. No evidence of major fitness costs due to the mutations in the SdhB subunit was found, which indicates the potential ability of the mutants to survive and compete with wild-type isolates. Our study suggests high risks for rapid widespread occurrence of B. cinerea populations resistant to the novel SDHIs unless appropriate rotation strategies are implemented immediately upon registration.

Understanding the genetic architecture of traits in breeding programs can be critical for making genetic progress. Important factors include the number of loci controlling a trait, allele frequencies at those loci, and allele effects in breeding germplasm. To this end, multiparental populations offer many advantages for quantitative trait locus (QTL) analyses compared to biparental populations. These include increased power for QTL detection, the ability to sample a larger number of segregating loci and alleles, and estimation of allele effects across diverse genetic backgrounds. Here, we investigate the genetic architecture of resistance to crown rot disease caused by Phytophthora cactorum in strawberry (Fragaria × ananassa), using connected full-sib families from a breeding population. Clonal replicates of > 1100 seedlings from 139 full-sib families arising from 61 parents were control-inoculated during two consecutive seasons. Subgenome-specific single nucleotide polymorphism (SNP) loci were mapped in allo-octoploid strawberry (2n = 8 × = 56), and FlexQTL software was utilized to perform a Bayesian, pedigree-based QTL analysis. A major locus on linkage group (LG) 7D, which we name FaRPc2, accounts for most of the genetic variation for resistance. Four predominant SNP haplotypes were detected in the FaRPc2 region, two of which are strongly associated with two different levels of resistance, suggesting the presence of multiple resistance alleles. The phenotypic effects of FaRPc2 alleles across trials and across numerous genetic backgrounds make this locus a highly desirable target for genetic improvement of resistance in cultivated strawberry.

The fungal genus Colletotrichum includes numerous important plant pathogenic species and species complexes that infect a wide variety of hosts. Its taxonomy is particularly complex because species’ phenotypes and genotypes are difficult to differentiate. Two notable complexes, C. acutatum and C. gloeosporioides, are known for infecting temperate fruit crops worldwide. Even species within these complexes vary in traits such as tissue specificity, aggressiveness, geographic distribution, and fungicide sensitivity. With few effective chemicals available to control these pathogens, and the persistent threat of fungicide resistance, there is a need for greater understanding of this destructive genus and the methods that can be used for disease management. This review summarizes current research on diseases caused by Colletotrichum spp. on major fruit crops in the United States, focusing on the taxonomy of species involved, disease management strategies, and future management outlook.

Strawberry growers in Florida suffer from a lack of efficient and accurate yield forecasts for strawberries, which would allow them to allocate optimal labor and equipment, as well as other resources for harvesting, transportation, and marketing. Accurate estimation of the number of strawberry flowers and their distribution in a strawberry field is, therefore, imperative for predicting the coming strawberry yield. Usually, the number of flowers and their distribution are estimated manually, which is time-consuming, labor-intensive, and subjective. In this paper, we develop an automatic strawberry flower detection system for yield prediction with minimal labor and time costs. The system used a small unmanned aerial vehicle (UAV) (DJI Technology Co., Ltd., Shenzhen, China) equipped with an RGB (red, green, blue) camera to capture near-ground images of two varieties (Sensation and Radiance) at two different heights (2 m and 3 m) and built orthoimages of a 402 m2 strawberry field. The orthoimages were automatically processed using the Pix4D software and split into sequential pieces for deep learning detection. A faster region-based convolutional neural network (R-CNN), a state-of-the-art deep neural network model, was chosen for the detection and counting of the number of flowers, mature strawberries, and immature strawberries. The mean average precision (mAP) was 0.83 for all detected objects at 2 m heights and 0.72 for all detected objects at 3 m heights. We adopted this model to count strawberry flowers in November and December from 2 m aerial images and compared the results with a manual count. The average deep learning counting accuracy was 84.1% with average occlusion of 13.5%. Using this system could provide accurate counts of strawberry flowers, which can be used to forecast future yields and build distribution maps to help farmers observe the growth cycle of strawberry fields.